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-year period and is funded by a Carlsberg Foundation Accomplish Grant to Prof. Nanna B. Karlsson. About the position This position is part of the research programme REGLA, investigating the physical
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qualifications: Applicants must hold a PhD degree in computer science, bioinformatics or similar. The applicant must be proficient in programming in Python and Java script. Have strong cooperation and
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qualifications: Applicants must hold a PhD degree in computer science, bioinformatics or similar. The applicant must be proficient in programming in Python and Java script. Have strong cooperation and
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level, e.g. in medical physics, physics, biomedical engineering or computer science. It is mandatory that your PhD degree is on a topic relevant for this specific position, e.g. in medical image-based
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
workshops. Qualifications Applicants must hold a PhD degree (or equivalent) in a relevant field. Suitable disciplinary backgrounds include but are not limited to: Computer Science, Data Science, Artificial
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program focusing on methodological as well as transferable skills, including dissemination, collaboration, and work planning CPPEM as a whole spans research from pharmacoepidemiology and clinical studies
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Offer Starting Date 1 Sep 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer
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. Applicants must have: A relevant PhD degree (Wireless Communications, or a related field) Demonstrated research experience in physical layer, multi-antenna technologies, medium access control of wireless
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copies to Aarhus BSS HR & PhD, Aarhus University, Bartholins Allé 16, DK-8000 Aarhus C. Read more about how to apply for an academic post at Aarhus BSS here The evaluation process After the application
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understanding of material science and electrical transport physics. Experience with electrical characterization of devices, ideally low-noise characterization of magnetometers. A strong drive to move